A Class of Stable Square-Root Nonlinear Information Filters

被引：33

作者：

Wang, Shiyuan ^{[1
,2
]}

Feng, Jiuchao ^{[3
]}

Tse, Chi K. ^{[2
]}

机构：

[1] Southwest Univ, Sch Elect & Informat Engn, Chongqing 400715, Peoples R China

[2] Hong Kong Polytech Univ, Dept Elect & Informat Engn, Hong Kong, Hong Kong, Peoples R China

[3] S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Guangdong, Peoples R China

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2014年 / 59卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Nonlinear estimation; nonlinear information filter; numerical stability; square-root decomposition;

D O I：

10.1109/TAC.2013.2294619

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Information filters can process nonlinear systems with uncertain prior knowledge, and the particular square-root form of adaptive filters can improve numerical stability. Based on a square-root decomposition of information matrix and an extra positive definite matrix, the unscented transform and the cubature rule are applied to the information filtering architecture for nonlinear estimation. A class of stable square-root nonlinear information filters is then proposed in this technical note. In addition, the boundedness of their estimation errors is also proven. Results from simulations of filtering a chaotic map demonstrate that the proposed square-root nonlinear filters can improve numerical stability, and has better filtering performance than other information filters.

引用

页码：1893 / 1898

页数：6

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